2014 47th Hawaii International Conference on System Sciences (2008)
Waikoloa, Big Island, Hawaii
Jan. 7, 2008 to Jan. 10, 2008
Wireless sensor applications (WSNs) are often required to simultaneously satisfy conflicting operational objectives (e.g., latency and power consumption). Based on an obser- vation that various biological systems have developed the mechanisms to overcome this issue, this paper proposes a biologically-inspired adaptation mechanism, called MON- SOON. MONSOON is designed to support data collection applications, event detection applications and hybrid appli- cations. Each application is implemented as a decentralized group of software agents, analogous to a bee colony (appli- cation) consisting of bees (agents). Agents collect sensor data and /or detect an event (a significant change in sen- sor reading) on individual nodes, and carry sensor data to base stations. They perform these data collection and event detection functionalities by sensing their surrounding en- vironment conditions and adaptively invoking biologically- inspired behaviors such as pheromone emission, reproduc- tion and migration. Each agent has its own behavior pol- icy, as a gene, which defines how to invoke its behaviors. MONSOON allows agents to evolve their behavior policies (genes) and adapt their operations to given objectives. Sim- ulation results show that MONSOON allows agents (WSN applications) to simultaneously satisfy conflicting objec- tives by adapting to dynamics of physical operational envi- ronments and network environments (e.g., sensor readings and node /link failures) through evolution.
Pruet Boonma, Junichi Suzuki, "MONSOON: A Coevolutionary Multiobjective Adaptation Framework for Dynamic Wireless Sensor Networks", 2014 47th Hawaii International Conference on System Sciences, vol. 00, no. , pp. 498, 2008, doi:10.1109/HICSS.2008.323